Basic Study
Copyright ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Oncol. Feb 24, 2021; 12(2): 95-102
Published online Feb 24, 2021. doi: 10.5306/wjco.v12.i2.95
Autosegmentation of cardiac substructures in respiratory-gated, non-contrasted computed tomography images
Mark Farrugia, Han Yu, Anurag K Singh, Harish Malhotra
Mark Farrugia, Anurag K Singh, Harish Malhotra, Department of Radiation Medicine, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14203, United States
Han Yu, Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14203, United States
Author contributions: Farrugia M participated in conceptualization, manual contouring, data analysis, figure construction, writing and editing; Yu H provided statistical support and review; Singh AK was involved in conceptualization and supervision; Malhotra H participated in conceptualization, supervision, software utilization, writing and editing.
Institutional review board statement: The study was reviewed and approved by the Roswell Park Comprehensive Cancer Center Institutional Review Board, No. EDR 171710.
Institutional animal care and use committee statement: The current project did not require any work with animal subjects.
Conflict-of-interest statement: No author claims any conflicts of interest.
Data sharing statement: No additional data are available.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See:
Corresponding author: Harish Malhotra, PhD, Assistant Professor, Department of Radiation Medicine, Roswell Park Comprehensive Cancer Center, Elm and Carlton Streets, Buffalo, NY 14203, United States.
Received: November 20, 2020
Peer-review started: November 20, 2020
First decision: December 3, 2020
Revised: December 7, 2020
Accepted: December 22, 2020
Article in press: December 22, 2020
Published online: February 24, 2021
Research background

Cardiotoxicity from thoracic radiotherapy can significantly contribute to treatment related morbidity and mortality. Despite this, cardiac substructures are not routinely delineated in thoracic radiation planning.

Research motivation

Autosegmentation of cardiac substructures would allow for relative dose calculation to these subsites without the added labor of manual definition.

Research objectives

To determine whether autosegmentation software can be successfully employed for the cardiac substructures in patients planned using respiratory gated, non-contrasted computed tomography (CT) imaging.

Research methods

This retrospective study included patients who underwent stereotactic body radiation therapy (SBRT) for inoperable, early-stage non-small cell lung cancer from 2007 to 2019. All patients were simulated via CT imaging with respiratory gating without intravenous contrast. A 20-patient atlas of the cardiac substructures was manually constructed and used to facilitate autosegmentation via MIM software. A total of three iterations of autosegmentations were completed, each using 10 patients. Generated structure quality was evaluated by degree of required manual edits and volume discrepancy between the autocontoured structures and its edited sister structure.

Research results

The great vessels and heart chambers were reliably autosegmented with most edits considered minor. In contrast, coronary arteries either failed to be autosegmented or the generated structures required major alterations necessitating deletion and manual definition. Similarly, the generated mitral and tricuspid valves were poor whereas the aortic and pulmonary valves required at least minor and moderate changes respectively. For the majority of subsites, the additional samples did not appear to substantially impact the quality of generated structures. Volumetric analysis between autosegmented and its manually edited sister structure yielded comparable findings to the physician-based assessment of structure quality.

Research conclusions

Our study indicated that the great vessels and heart chambers can be reliable autocontoured using MIM software. On the other hand, autosegmentation for valves is inconsistent and poor for coronary arteries. Anatomic variances and/or implanted hardware may impact the quality of autosegmentation.

Research perspectives

Radiation heart dose is an important dosimetric parameter however dose tolerances for the cardiac substructures in conventional therapy and SBRT are not well-established. Therefore, artificial intelligence based contouring programs allow dose to be calculated to the select cardiac subsites without the added labor of manual definition.